A Quantitative Assessment of the Aggregate Effects of the Franc

The graphical comparison of firms’ investment plans with the realized investment data, presented in section 6.4.1. , indicates that investment would have been higher in Switzerland in 2015 had the Franc shock not occurred. The DiD analysis, how-ever, does not allow to draw such conclusions, as it focuses on the relative causal effects of the Franc shock. Firms with negative net exposure may benefit from cheaper imported intermediates after the Franc shock, and thus increase invest-ments. The comparison of firms with positive and non-positive exposure may thus cumulate the negative effects on one group with the positive effects on the other.

We study the extent to which there is evidence for this in Figure 18. It shows esti-mates of the Franc shock effect on log gross fixed capital formation separately for firms with different degree of net exposure. The coefficients are estimated using firms with a net exposure close to zero (between -5% and 5%) as a reference cate-gory. The figure shows that firms with large negative net exposure do not invest more than firms with close to zero net exposure in 2015 and 2016. This appears to hold for most outcomes studied in this section, especially in 2015, which suggests that the positive investment effects from natural hedging through cheaper imported intermediates did not yet influence investment decisions in the first year after the shock. The large relative effects found in the previous sections appear to arise be-cause positively exposed firms reduce investment and not bebe-cause negatively ex-posed firms increase investment due to cheaper imported intermediates.

Figure 18: Investment Effects of the Franc Shock in 2015 and 2016 Depending on Firms’

Initial Net Exposure

Notes: The figure shows the estimated effects of the Franc shock on total investment in 2015 and 2016, depending on firms’ initial net exposure. The effects are estimated by regressing the outcome on an interaction between a dummy equal to one in 2015 and 2016 and indicators for the respective category of net exposure. The reference category is firms with net exposure between -5% and 5%.

Net exposure is firms’ initial export share in sales minus its initial import share in total costs.

In Table 14, we attempt to directly estimate the counterfactual investment of the average firm if the Franc shock had not occurred. To this end, we use a specifica-tion akin to the one in Figure 18, i.e. we augment our baseline model used with an interaction term that estimates a separate effect of the Franc shock for firms with negative exposure (firms with initial net exposure below -0.05) and firms with positive exposure (firms with initial net exposure above 0.05). Taking the point estimates of this estimation at face value, we can construct a rough estimate of the effect of the Franc shock on average investment of firms. Considering that firms with 𝐼[𝑠_𝑖> 5%] make up 23% of the sample, and reduce investment in 2015 and 2016 by 13.6% according to the estimation, while firms with 𝐼[𝑠^𝑖< −5%] repre-sent 48% of the sample but do not change investment substantially, the estimates imply that average nominal investment would have been 3% higher without the Franc shock.

These estimates are likely to underestimate the aggregate investment effect of the Franc shock because the shock also affected non-exposed firms through lower domestic demand. In particular, the Franc shock likely increased import competi-tion in the domestic markets. In column 2, we thus interact an indicator variable for the post-2015 period with the import penetration ratio of firms’ industries. The ratio is computed on the NACE 2-digit level and is also used in the previous sec-tions. Because our import penetration measure applies only to manufacturing in-dustries, the estimation is restricted to manufacturing. As expected, the interaction term is negative, suggesting that increased import competition depressed

invest-ment. Although the coefficient is not statistically significant, it is economically relevant.²⁸ The “total” effect of the Franc shock in this model, adding up the con-tribution from the export, imported intermediates, and import competition channel, is -8%. Note that these are rough estimates, as they are estimated with large stand-ard errors, depend on the specification, and on the exact thresholds chosen to as-sign firms into categories of net exposure. However, they suggest non-negligible negative effects of the Franc shock on investment of the average firm participating in the KOF investment survey.

Table 14: Accounting for the Effect of the Franc Shock on the Aggregate Economy

(1) (2)

Investment Investment

variables Manufacturers

I[t>=2015] x I[Net exposure>5%] -0.136** -0.133

(0.061) (0.095)

I[t>=2015] x I[Net exposure<-5%] -0.007 0.013

(0.054) (0.096)

I[t>=2015] x IP -0.051

(0.076)

Observations 14,236 6,093

R-squared 0.007 0.016

Number of firms 4,201 1,812

Period FE Yes Yes

Firm FE Yes Yes

Share exposed 0.23 0.42

Share negatively exposed 0.48 0.41

Average IP . 0.56

Average effect -0.03 -0.08

Notes: The table shows results from our baseline FE regression model. The estimation period is 2012-2016. The dependent variable is log gross fixed capital formation (total investment). All investment figures are measured at current prices. Net exposure is firms’ initial export share in sales minus its initial import share in total costs. “IP” measures the industry-specific import penetration ratio, constructed from Swiss trade data for manufacturing industries. Standard errors are clustered on the firm level. *** p<0.01, ** p<0.05, * p<0.1

28 As the average import penetration ratio is 56%, it suggests that the Franc shock depressed nominal investment by 2.5% in the average firm through increased import penetration.